Exploratory Data Analysis for the Common Objects In Context(COCO) Dataset

Introduction

COCO dataset, which stands for "Common Objects in Context", is a large-scale dataset for object detection, segmentation and captioning tasks in computer vision.

YOLO, which stands for "You Only Look Once" is a deep learning algorithm for real-time object detection. It consist of a neural network that takes input image/video and outputs bounding boxes and class probabilities for the objects detectd in the images

YOLO model is trained on the COCO dataset to learn to detect objects in images and videos accurately.

This notebook is designed to provide insights on the COCO 2017 dataset

Dataset can be downloaded from the COCO dataset Website

Please Note that the dataset is already split from the source(coco dataset website) into training, testing and validation set, it consists of image files in jpg format and annotation files in json format

DATASET SUMMARY COUNT FOR TRAIN, TEST AND VALAIDATION IMAGES

Total number of unique object classes: 80

TRAINING DATASET SUMMARY

Total number of images in training folder: 118287
Total number of annotations in training dataset: 860001
Number of person annotations: 262465
Number of face annotations: 0

Category Distribution for Training Data:
Object Distribution for Training Data:

TESTING DATASET SUMMARY

Total number of images in test folder: 40670

VALIDATION DATASET SUMMARY

Total number of images in validation folder: 5000
Total number of annotations in validation dataset: 36781
Number of person annotations: 11004
Number of face annotations: 0

Category Distribution for Validation Data:
Object for Validation Data:

VISUALIZATION OF SAMPLE IMAGES AND THEIR ANNOTATIONS, ALSO FIND BELOW A LIST OF ALL 80 CATEGORIES IN THE DATASET

List of all categories:
person
bicycle
car
motorcycle
airplane
bus
train
truck
boat
traffic light
fire hydrant
stop sign
parking meter
bench
bird
cat
dog
horse
sheep
cow
elephant
bear
zebra
giraffe
backpack
umbrella
handbag
tie
suitcase
frisbee
skis
snowboard
sports ball
kite
baseball bat
baseball glove
skateboard
surfboard
tennis racket
bottle
wine glass
cup
fork
knife
spoon
bowl
banana
apple
sandwich
orange
broccoli
carrot
hot dog
pizza
donut
cake
chair
couch
potted plant
bed
dining table
toilet
tv
laptop
mouse
remote
keyboard
cell phone
microwave
oven
toaster
sink
refrigerator
book
clock
vase
scissors
teddy bear
hair drier
toothbrush